计算机工程与应用2012，Vol.48Issue(10)：47-53,7.DOI:10.3778/j.issn.1002-8331.2012.10.012
改进的NSGA-Ⅱ算法及其在星座优化设计中的应用
Improved NSGA-Ⅱ algorithm and its application in optimization of satellite constellation
摘要
Abstract
In order to overcome the shortages of Simulated Binary Crossover(SBX) operator, convergence speed and population diversity of NSGA-Ⅱ, this paper applies the opposition-based learning mechanism to the initialization and evolution process of NSGA-Ⅱ algorithm. In addition, the paper introduces an improved arithmetic crossover operator as well. The convergence and diversity of the proposed algorithm on the series of ZDT test bench-marks are evaluated and the results show that the improved NSGA-Ⅱ algorithm is better than the traditional NSGA-II on converge speed, convergence and diversity. The paper applies the proposed algorithm to the optimization of satellite constellation design and the results indicate that the improved algorithm is very effective on this application.关键词
多目标优化/NSGA-Ⅱ算法/反向学习/卫星星座Key words
multi-objective optimization/ NSGA-Ⅱ/ opposition-based learning/ satellite constellation分类
信息技术与安全科学引用本文复制引用
肖宝秋,刘洋,戴光明..改进的NSGA-Ⅱ算法及其在星座优化设计中的应用[J].计算机工程与应用,2012,48(10):47-53,7.基金项目
国家自然科学基金项目(No.60873107). （No.60873107）
